Monolithic vs. Microservices Architecture

Every software system eventually faces the same challenge: how to grow as more users join.

An approach that works well for a small startup can later become the biggest obstacle to scaling. Choosing the right architecture is crucial for engineers because it impacts how quickly the system scales, its stability, and how product teams can continually improve it.

This is also why interviewers often ask about monoliths and microservices to test our understanding of the trade-offs in scaling systems. This lesson explores that journey, starting with the monolith.

Monolithic architecture

A monolithic architecture is the traditional model of building an application as a single, indivisible unit. All components, from the user interface and business logic to the data access layer, are developed, deployed, and scaled together.

For early-stage products or small applications, this approach is often ideal. Its primary benefits include:

• Simplicity in development: A unified codebase in a single repository makes it easy to set up, write code, and test.

• Ease of deployment: The entire application is deployed as a single artifact, simplifying the release process.

• Straightforward debugging: Since all code runs within a single process, tracing a request or bug does not involve inter-service communication, which simplifies debugging compared to distributed systems. However, as the monolith grows, overall complexity may still make debugging challenging.

However, as the application grows, this simplicity gives way to significant challenges.

The most common limitation is tight coupling, a state where components are so highly dependent on each other that a small change in one part of the system can have unintended consequences elsewhere. This slows down development as the codebase becomes harder to understand and modify.

Scaling becomes an all-or-nothing proposition; you must scale the entire application even if only one small feature is experiencing high traffic. These growing pains often lead teams to seek a more structured approach.

The limitations of a classic monolith do not always necessitate a complete rewrite. A more structured, intermediate step can often provide the needed flexibility without the full complexity of distributed systems. This approach is known as the modular monolith.

Modular monoliths (structured flexibility)

A modular monolith is an evolution of the traditional monolith.

It remains a single deployable unit but is internally structured into distinct, independent modules. Each module is responsible for a specific business domain, like user management, payments, or inventory. While they share the same runtime and database, they communicate through well-defined, internal APIs or interfaces.

The primary goal is to enforce logical boundaries within the codebase, achieving a strong separation of concerns. This is similar to organizing a single-room restaurant into designated sections, including a kitchen area, a dining area, and a payment counter, each with clear responsibilities, all within the same building.

Key advantages over a classic monolith include:

• Improved codebase organization: The system is easier to navigate and understand, as code related to a specific domain is grouped together.

• Better team scaling: Different teams can work on separate modules with less risk of interfering with each other’s work.

• Easier testing: Modules can be tested in isolation more effectively.

• Paves the way for microservices: If needed, a well-defined module can be more easily extracted and turned into an independent microservice later.

The main drawback is that it is still a monolith.

All modules are deployed together, so a failure in one module can potentially bring down the entire application. There is also a risk that developers will bypass the defined interfaces and create hidden dependencies between modules, thereby undermining the architecture.

Despite these issues, the modular monolith is an excellent choice for teams that need more structure than a classic monolith but are not ready for the operational overhead of a fully distributed system.

Note: A key discipline for maintaining a modular monolith is to prevent direct data access between modules. One module should never directly query another module’s database tables, it must always go through its public API.

While the modular monolith adds much-needed structure, it is still a single deployable unit. For organizations that require true independent scaling and deployment for their teams, the final step in this evolution is to embrace distributed systems.

Microservices architecture

In a microservices architecture, an application is broken down into a collection of small, autonomous services.

Each service runs independently and communicates with others over a network, typically using APIs. This is akin to replacing a single large restaurant with a food court, where each stall operates as an independent business.

Instead of containing all responsibilities in a single monolith, microservices split them across multiple services.

This architectural style offers significant benefits, which is why companies like Netflix and Uber famously adopted it to manage their massive scale.

• Independent deployment: Teams can deploy their services on their own schedules, without needing to coordinate with other teams.

• Technology freedom: Each service can be built with the programming language and database best suited for its specific task.

• Improved fault isolation: A failure in one service does not necessarily bring down the entire application, improving overall resilience.

• Granular scalability: Individual services can be scaled independently based on their specific resource needs.

However, these benefits come with a steep increase in complexity. Moving from a single system to a network of services introduces a new set of challenges that must be managed, such as:

• Inter-service communication: Services require a reliable method of communication over an unreliable network.

• Data management: Maintaining data consistency across multiple services is a complex task. This often involves concepts like eventual consistencyA consistency model in distributed computing which guarantees that, if no new updates are made to a given data item, all accesses to that item will eventually return the last updated value..

• Operational overhead: Deploying, monitoring, and debugging a distributed system requires sophisticated tools and expertise in areas such as service discovery and distributed tracing.

Now, let’s compare these architectures side by side to better understand their respective trade-offs.

The table above highlights the progression in flexibility and the corresponding increase in complexity. For many organizations, the final step in this evolution is to embrace distributed systems. The decision to adopt a particular architecture is not purely technical; it depends heavily on the business context and the team.

Understanding how to weigh these factors is a critical engineering skill.

How to approach architecture choices

Choosing the right architecture involves balancing trade-offs based on a specific context. There is no universally “best” architecture, only the most appropriate one for a given problem at a given time. When making this decision, consider the following criteria:

• Team size and structure: A small team can move quickly with a monolith. Larger organizations may benefit from the autonomy that microservices provide, as described by Conway’s Lawhttps://en.wikipedia.org/wiki/Conway%27s_law, which states that organizations design systems that mirror their own communication structure.

• Business stage: An early-stage startup needs to iterate and ship features fast; a monolith is often the right choice. A mature company with a complex product and high scale might need the flexibility of microservices.

• Scaling needs: If different parts of an application have vastly different scaling requirements, microservices can be a more cost-effective solution.

• Operational maturity: Do you have the infrastructure, tooling, and expertise to manage a distributed system? If not, the operational burden of microservices can outweigh the benefits.

A common and sensible path is to start with a well-structured modular monolith.

This approach provides a solid foundation with clear domain boundaries, allowing for rapid initial development while maintaining the option to gradually migrate to microservices later. You can identify modules that are performance-critical or require frequent updates and strategically extract them as independent services over time.

This incremental approach de-risks the migration, allowing the team to learn and adapt as they proceed.

If you’re not sure how to do this, click the “Want to know the correct answer?” button.

Conclusion

The evolution from monoliths to modular monoliths and microservices reflects the need for scalability and team autonomy.

Monoliths initially offer speed and simplicity, while modular monoliths add structure with minimal operational costs. Microservices enable independent scaling but introduce high complexity. The best choice depends on the product’s stage, team size, and capabilities, rather than simply following the latest trend.

In our next lesson, we will explore another critical aspect of design: defining the functional and non-functional requirements that shape these architectural choices.